Advancements in Artificial Intelligence for Precision Agriculture: A Comprehensive Review

Abstract

Artificial Intelligence (AI) hasgrown rapidly over the years and had a tremendous impact on sectors like agriculture. This paper is a review of the progress in AI and its deep learning approaches used in precision agriculture.  Precision agriculture seeks to increase agricultural yield and minimize negative environmental effects through the use such as machine learning (ML), computer vision, Internet of Things(IoT) and automation of technologies This article discusses the different AI strategies applied to overcome issues such as crop yield forecasting, pest  detection, weedcontrol, effectiveness of resources recycling and automation in farming operations to solving issues.  It also  explores AI combined with sensor networks, drones, and robots to develop intelligent systems which can perform real-time analysis and take decisions . The role of deep learning, CNNs and reinforcement learning transforming precision agriculture applications is also discussed in the review. While the possibilities for increased efficiency through AI in agriculture are great, the paper acknowledges issues including access to data and a rural digital divide. The  implementation costs critique potential, highlights the providing new solutions to address worldwide food security and environmental challenges